The controlled source electromagnetic survey method in a marine environment uses an applied source for mapping sub-seafloor resistivity variations; see, for example, U.S. Pat. No. 6,603,313 to Srnka. FIG. 1 is a schematic diagram of such a survey, with electromagnetic source 11 connected by cable to a vessel and receivers 12 located in the ocean, and often on the seafloor 13. The measured fields are analyzed to investigate the sub-sea floor structures of the earth's interior.
The electromagnetic signals recorded by receivers consist of electromagnetic fields 21, 22 and 23 that travel through the earth 33, seawater 32, and air 31, respectively, as illustrated in FIG. 2. The signal 23 that travels partly through air is called an “air wave.” In addition to this controlled-source air wave, there is magnetotelluric (MT) noise propagating through the air caused, for example, by ionospheric disturbances. Offshore controlled-source electromagnetic geophysical surveys are normally operated at frequencies below 1.0 KHz. It is well known that, in this quasi-static frequency regime, penetration of electromagnetic waves into a medium varies inversely with both the frequency of the wave and the conductivity of the medium. This result follows from the theory of skin effect phenomena (J. A. Stratton, Electromagnetic Theory, page 504, MacGraw-Hill (1941)). Since the seawater is much more conductive than both air and the earth, electromagnetic signals through the seawater decay much faster than through the air and the earth. So, for source and receiver offsets longer than approximately twice the seawater depth, the recorded electromagnetic fields mainly come through the air and the earth. However, only the signals traveling through the earth provide information of the sub-sea floor structures of the earth's interior. For deep sub-sea floor targets 34, electromagnetic fields need to be generated at low frequencies to ensure that the transmitted electromagnetic signals 25 penetrate to the target depth. Unfortunately, for “shallow” water depth relative to the target depth and at low frequencies, the air wave signal may be dominant at receivers 12 with long offsets to the source 11 so that, the target signal is hardly distinguishable. Obviously, conditions are best for CSEM prospecting when signal 25 dominates the combined effects of signals 21, 22 and 23.
Air wave interference is a problem when measurements are made in the frequency domain, i.e., when the source continues to transmit its signals while data are being collected at the receivers. The simplest source signal is a sinusoidal signal with a selected frequency. For operational efficiency, multiple frequencies can be transmitted at the same time in the form of a complex waveform, such as a square wave. A complement to the frequency domain CSEM is the time domain CSEM. In time domain CSEM, the source is turned on and then turned off after a desired wave form is transmitted (for example, a pulse, a boxcar, or a step function). The air wave may not be a problem in time domain CSEM because the air wave will be recorded at an earlier time, separated from target signals. Frequency domain CSEM has certain advantages over time domain CSEM including the availability of more sophisticated modeling and inversion software, more familiarity with the results, and higher-quality data. As persons skilled in the art will understand, notwithstanding the preceding observations, all CSEM data are actually obtained in the time domain, i.e., they are collected by a recording device as a more or less continuous stream of numbers, with the independent variable being time. What distinguishes frequency domain CSEM is the way the experiment is conducted (continuous source) and the methods used to analyze and interpret the data whereby the data are decomposed into individual frequency components, e.g., Fourier analysis.
The air wave effect can be easily illustrated using a simple one-dimensional (1D) layered model. As shown in FIG. 3, from top to bottom, the model consists of five layers: non-conductive air 31, seawater 32 (conductivity=3.0 Siemens/m, depth to be varied in examples below), mud rocks 33 (1.0 Siemen/m, 1.0 km thick), resistive reservoir layer 34 (0.01 Siemen/m, 100.0 m thick), and basement 35 (1.0 Siemen/m). If the resistive layer 34 is the target and is removed from this model, a new model results and may be defined as the background model of the original model. A unit horizontal electric dipole source 11 directed in the x-axis (HEDx) is towed in the direction of the x-axis and 50 m above the seafloor. A seafloor receiver 12 is located right below the mid point of the source tow line (not shown in FIG. 3).
FIGS. 4A-4C are graphs of the amplitude of the x-component of electric fields (Ex) vs. source-receiver separation in the x-direction for both this 1D model and its background model. The seawater depth is 5.0 km in FIG. 4A, 1.0 km in FIG. 4B, and 100 m in FIG. 4C. FIGS. 4D-4F show the corresponding “unwrapped” phase, for the same three seawater depths. Unwrapped phase is obtained by changing absolute jumps greater than π to their 2π complement. The curves of small circles represent data from the 1D model and the solid lines are from the background model. For the seawater depth of 5 km (FIGS. 4A and 4D), there is negligible air wave effect on data from both models for all source and receiver separations plotted in the figure. Large separation between the 1D model's curves 41 and 43 and its background curves 42 and 44 indicates that the signal from the resistive layer buried 1.0 km below the seafloor is significant when the source-receiver separation is larger than ˜2 or 3 km. (The lack of separation between the model and background curves for small source-receiver spacing is due to the correspondingly low attenuation of the water path 22 and the seafloor path 21. Contribution from those two signals dominates the received signal for receivers with small offset (source-receiver separation), even with the target layer in the model.) When the seawater depth is decreased to 1.0 km (FIGS. 4B and 4E), the separation between these two curves shrinks significantly because of the air wave effect, i.e., the path 23 in FIG. 2 now travels through much less water and consequently attenuation of the unwanted air wave is greatly diminished. This effect is magnified with increasing offset. At offsets longer than ˜6 or 7 km, the air wave effect dominates the received signal for the background model. This can be seen from the background curves 46 and 48 in FIGS. 4B and 4E, in particular the break in slope of the amplitude curve 46 around 6 km and the constant phase of the phase curve 48 beyond ˜7 km. However, no such features appear in the data curves 45 and 47 for the 1D model with the buried resistive layer because the signal from the buried resistive layer is still stronger than the air wave effect for this 1D model with 1.0 km water depth. This no longer holds when the seawater depth is 100 m, for which FIG. 4C shows that model data with and without the resistive reservoir layer are hardly distinguishable in amplitude for all offsets. (The significant departure between the two phase curves of FIG. 4F for offsets greater than ˜3 km is primarily an effect of the infinitely extended 1D model used rather than being due to signal from the target; this effect would be essentially eliminated with a more realistic model.) Matters would be even worse for field data with MT noise. This implies that the air wave effect dominates the received signal even though the signal from the sub seafloor target is strong. The results from this example clearly demonstrate the problem of the air wave effect.
Thus, for typical marine CSEM acquisition, the thick layer of conductive water above the source and receivers serves the important purpose of attenuating the air-wave path as well as attenuating the atmospheric MT noise. In the shallow-water case, however, the air wave and MT noise can have significant amplitude that masks the desired signals. Shallow water is defined as having a small number of skin depths and is thus a function of the source frequency. (The electromagnetic “skin depth” is a function of frequency [inversely proportional to the square root of the frequency] and determines the decay, and hence the effective depth of penetration, of an electromagnetic signal in a conductive medium such as salt water.) Lower frequencies that are required for greater earth penetration also require greater water depths to adequately attenuate the air-wave path.
Ambient MT noise is uncorrelated with the controlled source signal. As a result, typical approaches to minimize the effect of this noise involve doing more repetitions of the source waveform or using higher source energy levels.
Several approaches have been attempted to minimize controlled-source EM air-wave noise. In some approaches, different aspects of the data are examined while in others a processing method is used to remove air-wave noise. While all of these methods work to some extent, the existence of a very large air-wave component means that inaccuracies in the methods can lead to substantial residual noise. In contrast, the present invention actually reduces the EM energy that makes it into the air and the noise is never recorded.
In the category of examining different data components, one could use EZ (vertical field) data. Most air-wave related noise in the water is oriented in the Ex (in-line horizontal) direction. Although Ez can be a helpful addition, its drawbacks include the smaller signal strength (causing greater MT noise problems), the remaining air-wave effect that still occurs in Ez, and the additional air-wave noise that is recorded on an Ez receiver when it is not perfectly vertical.
A similar approach is to use a vertical electric dipole source, since it is known that a VED will generate a very small air wave. By reciprocity, there are similar issues (e.g., small signal, sensitivity to alignment). Also, there may be logistics issues in operating a moving vertical electric source in the ocean.
Another component-related approach (see G.B. Patent No. 2411006 to MacGregor, et al.), emphasizes the use of the vertical gradient of the horizontal field. The required data can be obtained with vertically separated receivers or sources. The issues in this approach are similar to the previous examples. A vertical gradient d/dz(Ex) is a difference of two, small, comparable signals. The result is a very small signal that could have substantial ambient-noise problems. The air-wave effect is also not completely removed.
In the category of processing approaches, air-wave contaminated data are recorded and then an attempt is made to minimize the noise by subsequent processing. In one example, Lu et al. in U.S. Provisional Patent Application No. 60/482,681 use a 1D modeling-based approach to estimate the air wave for later subtraction. MT noise in the field data, however, can compromise the results leaving residual air-wave effects.
In another processing approach, Amundsen (WO 2003/100467) proposed decomposing EM fields into up going and down going components and using the up going component to derive the nature of the subsurface. This decomposition is an approximation and coupled with data noise can lead to incomplete airwave suppression.